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<a href="_simple_nearest_neighbors_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Efficient brute force implementation of nearest neighbors.</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \author      O.Krause</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \date        2012</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * </span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * </span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * </span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> *</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> */</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#ifndef SHARK_ALGORITHMS_NEARESTNEIGHBORS_SIMPLENEARESTNEIGHBORS_H</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#define SHARK_ALGORITHMS_NEARESTNEIGHBORS_SIMPLENEARESTNEIGHBORS_H</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span> </div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_nearest_neighbors_8h.html">shark/Algorithms/NearestNeighbors/AbstractNearestNeighbors.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_metric_8h.html">shark/Models/Kernels/AbstractMetric.h</a>&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="preprocessor">#include &lt;<a class="code" href="_open_m_p_8h.html">shark/Core/OpenMP.h</a>&gt;</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="preprocessor">#include &lt;algorithm&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span> </div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span> </div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment"></span> </div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">///\brief Brute force optimized nearest neighbor implementation</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment">///</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment">///Returns the labels and distances of the k nearest neighbors of a point </span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">/// The distance is measured using an arbitrary metric</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputType, <span class="keyword">class</span> LabelType&gt;</div>
<div class="foldopen" id="foldopen00051" data-start="{" data-end="};">
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html">   51</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_simple_nearest_neighbors.html" title="Brute force optimized nearest neighbor implementation.">SimpleNearestNeighbors</a>:<span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_nearest_neighbors.html" title="Interface for Nearest Neighbor queries.">AbstractNearestNeighbors</a>&lt;InputType,LabelType&gt;{</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_nearest_neighbors.html" title="Interface for Nearest Neighbor queries.">AbstractNearestNeighbors&lt;InputType,LabelType&gt;</a> <a class="code hl_class" href="classshark_1_1_abstract_nearest_neighbors.html" title="Interface for Nearest Neighbor queries.">base_type</a>;</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#a34c2838b82d29e9f725bef18d3540514">   55</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType, LabelType&gt;</a> <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#a34c2838b82d29e9f725bef18d3540514">Dataset</a>;</div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#ac39c0a94032d08b667e3cb692f514fbd">   56</a></span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_metric.html" title="Base-class for metrics.">AbstractMetric&lt;InputType&gt;</a> <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ac39c0a94032d08b667e3cb692f514fbd">Metric</a>;</div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#ae85bcee60ffdda60be8830e682785b9c">   57</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_key_value_pair.html" title="Represents a Key-Value-Pair similar std::pair which is strictly ordered by it&#39;s key.">base_type::DistancePair</a> <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ae85bcee60ffdda60be8830e682785b9c">DistancePair</a>;</div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#ad878c943fb9776f495b796d718e3a099">   58</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;InputType&gt;::type</a> <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ad878c943fb9776f495b796d718e3a099">BatchInputType</a>;</div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment"></span> </div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">    /// \brief Constructor.</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment">    /// \par Construct a &quot;brute force&quot; nearest neighbors search algorithm</span></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">    /// from data and a metric. Refer to the AbstractMetric class for details.</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment">    /// The &quot;default&quot; Euclidean metric is realized by providing a pointer to</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="comment">    /// an object of type LinearKernel&lt;InputType&gt;.</span></div>
<div class="foldopen" id="foldopen00066" data-start="{" data-end="}">
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#ac5425f13309ffab8422d344accddd3fa">   66</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_simple_nearest_neighbors.html#ac5425f13309ffab8422d344accddd3fa" title="Constructor.">SimpleNearestNeighbors</a>(<a class="code hl_class" href="classshark_1_1_labeled_data.html">Dataset</a> <span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_simple_nearest_neighbors.html#a87bb8ea903edac0d8a5ad560be47f47d" title="Direct access to the underlying data set of nearest neighbor points.">dataset</a>, <a class="code hl_class" href="classshark_1_1_abstract_metric.html">Metric</a> <span class="keyword">const</span>* metric)</div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>    :m_dataset(<a class="code hl_function" href="classshark_1_1_simple_nearest_neighbors.html#a87bb8ea903edac0d8a5ad560be47f47d" title="Direct access to the underlying data set of nearest neighbor points.">dataset</a>), mep_metric(metric){</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span>        this-&gt;<a class="code hl_variable" href="classshark_1_1_abstract_nearest_neighbors.html#a71d274e64e2eff7e1f72fa4fe3fb3473">m_inputShape</a>=dataset.<a class="code hl_function" href="group__shark__globals.html#ga134d41e34c69c494346367a570bf4ff8" title="Returns the Shape of the inputs.">inputShape</a>();</div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span>    }</div>
</div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span><span class="comment"></span> </div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span><span class="comment">    ///\brief Return the k nearest neighbors of the query point.</span></div>
<div class="foldopen" id="foldopen00072" data-start="{" data-end="}">
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#a389a29728ce4a6d7e50e2b94d449eb87">   72</a></span><span class="comment"></span>    std::vector&lt;DistancePair&gt; <a class="code hl_function" href="classshark_1_1_simple_nearest_neighbors.html#a389a29728ce4a6d7e50e2b94d449eb87" title="Return the k nearest neighbors of the query point.">getNeighbors</a>(<a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ad878c943fb9776f495b796d718e3a099">BatchInputType</a> <span class="keyword">const</span>&amp; patterns, std::size_t k)<span class="keyword">const</span>{</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span>        std::size_t numPatterns = <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(patterns);</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>        std::size_t maxThreads = std::min(<a class="code hl_define" href="_open_m_p_8h.html#afe4c8d5e3dea340345071efe7bf69a0a">SHARK_NUM_THREADS</a>,m_dataset.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>());</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>        <span class="comment">//heaps of key value pairs (distance,classlabel). One heap for every pattern and thread.</span></div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>        <span class="comment">//For memory alignment reasons, all heaps are stored in one continuous array</span></div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        <span class="comment">//the heaps are stored such, that for every pattern the heaps for every thread</span></div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        <span class="comment">//are forming one memory area. so later we can just merge all 4 heaps using make_heap</span></div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>        <span class="comment">//be aware that the values created here allready form a heap since they are all</span></div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>        <span class="comment">//identical maximum distance.</span></div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span>        std::vector&lt;DistancePair&gt; heaps(k*numPatterns*maxThreads,<a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ae85bcee60ffdda60be8830e682785b9c">DistancePair</a>(std::numeric_limits&lt;double&gt;::max(),LabelType()));</div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span>        <span class="keyword">typedef</span> <span class="keyword">typename</span> std::vector&lt;DistancePair&gt;::iterator iterator;</div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span>        <span class="comment">//iterate over all batches of the training set in parallel and let</span></div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span>        <span class="comment">//every thread do a KNN-Search on it&#39;s subset of data</span></div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span>        <a class="code hl_define" href="_open_m_p_8h.html#a8a63d79e2c3625260e6092d933f21a98" title="Set of macros to help usage of OpenMP with Shark.">SHARK_PARALLEL_FOR</a>(<span class="keywordtype">int</span> b = 0; b &lt; (int)m_dataset.<a class="code hl_function" href="group__shark__globals.html#gaca4b1e6083184385dba76a21b4c1d42b" title="Returns the number of batches of the set.">numberOfBatches</a>(); ++b){</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>            <span class="comment">//evaluate distances between the points of the patterns and the batch</span></div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>            RealMatrix distances=mep_metric-&gt;<a class="code hl_function" href="classshark_1_1_abstract_metric.html#a249ddd25ea56bc592ea2f8386070714d" title="Computes the squared distance in the kernel induced feature space.">featureDistanceSqr</a>(patterns,m_dataset.<a class="code hl_function" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">batch</a>(b).input);</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>            </div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno">   89</span>            <span class="comment">//now update the heaps with the distances</span></div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno">   90</span>            <span class="keywordflow">for</span>(std::size_t p = 0; p != numPatterns; ++p){</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span>                std::size_t <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a> = distances.size2();</div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span>                </div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>                <span class="comment">//get current heap</span></div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span>                std::size_t heap = p*maxThreads+<a class="code hl_define" href="_open_m_p_8h.html#a24697345975eb5504b786009159a1f5b">SHARK_THREAD_NUM</a>;</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>                iterator heapStart=heaps.begin()+heap*k;</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>                iterator heapEnd=heapStart+k;</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>                iterator biggest=heapEnd-1;<span class="comment">//position of biggest element</span></div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>                </div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span>                <span class="comment">//update heap values using the new distances</span></div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>                <span class="keywordflow">for</span>(std::size_t i = 0; i != <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>; ++i){</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>                    <span class="keywordflow">if</span>(biggest-&gt;key &gt;= distances(p,i)){</div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span>                        <span class="comment">//push the smaller neighbor in the heap and replace the biggest one</span></div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>                        biggest-&gt;key=distances(p,i);</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>                        biggest-&gt;value=<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(m_dataset.<a class="code hl_function" href="group__shark__globals.html#ga192f5eced10acf38f3ae723a3c400d98">batch</a>(b).label,i);</div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>                        std::push_heap(heapStart,heapEnd);</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>                        <span class="comment">//pop biggest element, so that </span></div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>                        <span class="comment">//biggest is again the biggest element</span></div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span>                        std::pop_heap(heapStart,heapEnd);</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>                    }</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>                }</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span>            }</div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span>        }</div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span>        std::vector&lt;DistancePair&gt; results(k*numPatterns);</div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span>        <span class="comment">//finally, we merge all threads in one heap which has the inverse ordering</span></div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        <span class="comment">//and create a class histogram over the smallest k neighbors</span></div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>        <span class="comment">//std::cout&lt;&lt;&quot;info &quot;&lt;&lt;numPatterns&lt;&lt;&quot; &quot;&lt;&lt;maxThreads&lt;&lt;&quot; &quot;&lt;&lt;k&lt;&lt;std::endl;</span></div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span>        <a class="code hl_define" href="_open_m_p_8h.html#a8a63d79e2c3625260e6092d933f21a98" title="Set of macros to help usage of OpenMP with Shark.">SHARK_PARALLEL_FOR</a>(<span class="keywordtype">int</span> p = 0; p &lt; (int)numPatterns; ++p){</div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>            <span class="comment">//find range of the heaps for all threads</span></div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>            iterator heapStart=heaps.begin()+p*maxThreads*k;</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>            iterator heapEnd=heapStart+maxThreads*k;</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>            iterator neighborEnd=heapEnd-k;</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>            iterator smallest=heapEnd-1;<span class="comment">//position of biggest element</span></div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>            <span class="comment">//create one single heap of the range with inverse ordering</span></div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>            <span class="comment">//takes O(maxThreads*k)</span></div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span>            std::make_heap(heapStart,heapEnd,std::greater&lt;DistancePair&gt;());</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>            </div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>            <span class="comment">//create histogram from the neighbors</span></div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>            <span class="keywordflow">for</span>(std::size_t i = 0;heapEnd!=neighborEnd;--heapEnd,--smallest,++i){</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>                std::pop_heap(heapStart,heapEnd,std::greater&lt;DistancePair&gt;());</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>                results[i+p*k].key = smallest-&gt;key;</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>                results[i+p*k].value = smallest-&gt;value; </div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>            }</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>        }</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>        <span class="keywordflow">return</span> results;</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>    }</div>
</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span><span class="comment"></span> </div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="comment">    /// \brief Direct access to the underlying data set of nearest neighbor points.</span></div>
<div class="foldopen" id="foldopen00138" data-start="{" data-end="}">
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno"><a class="line" href="classshark_1_1_simple_nearest_neighbors.html#a87bb8ea903edac0d8a5ad560be47f47d">  138</a></span><span class="comment"></span>    <a class="code hl_class" href="classshark_1_1_labeled_data.html" title="Data set for supervised learning.">LabeledData&lt;InputType,LabelType&gt;</a><span class="keyword">const</span>&amp; <a class="code hl_function" href="classshark_1_1_simple_nearest_neighbors.html#a87bb8ea903edac0d8a5ad560be47f47d" title="Direct access to the underlying data set of nearest neighbor points.">dataset</a>()<span class="keyword">const </span>{</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>        <span class="keywordflow">return</span> m_dataset;</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>    }</div>
</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span> </div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>    <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#a34c2838b82d29e9f725bef18d3540514">Dataset</a> m_dataset;                        <span class="comment">///&lt; data set of nearest neighbor points</span></div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>    <a class="code hl_typedef" href="classshark_1_1_simple_nearest_neighbors.html#ac39c0a94032d08b667e3cb692f514fbd">Metric</a> <span class="keyword">const</span>* mep_metric;                 <span class="comment">///&lt; metric for measuring distances, usually given by a kernel function</span></div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>};</div>
</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span> </div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span> </div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>}</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span><span class="preprocessor">#endif</span></div>
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